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Bryan McLachlan | How AI can help insurers excel in the moment of truth

Bryan McLachlan | How AI can help insurers excel in the moment of truth
09-03-23 / Bryan McLachlan

Bryan McLachlan | How AI can help insurers excel in the moment of truth

Most people have few interactions with their insurer besides getting a claims schedule with their premium adjustment every year and seeing their debit order go through at the end of each month. But that changes when their home is robbed, their car gets dinged, or the family’s breadwinner dies in an accident, and they need to make a claim.

Claims is the moment of truth in insurance, when the insurer is called upon to make good on the promises in its policy. It’s also usually a moment where the customer is annoyed, worried, perhaps even distraught, and is looking to their insurance company to help them as quickly as possible. Getting claims right or wrong is the difference between keeping a customer for life or losing them for good and getting a good or bad reputation by word of mouth.

Yet insurers also need to adjudicate claims carefully to minimise the risks of leakage, wastage and outright fraud. By some estimates, fraud costs the South African insurance industry as much as R6 billion to R8 billion per year. Sources of waste and fraud are numerous: from customers embellishing or falsifying claims to suppliers inflating their invoices.

Conflicting imperatives

The need to minimise fraud to protect the insurer’s financial sustainability and keep insurance premiums low thus often conflicts with the imperative to be there for the customer in their time of need. Minimising leakage and fraud means scrutinising each claim carefully, but offering a good customer experience means processing the claim as fast and with as little friction as possible.

What’s more, claims processes in many South African insurance companies remain largely paper-based, meaning that the administrative costs of processing claims can be steep. A reliance on manual processes in the absence of end-to-end digitalisation also means that claims processing can be error-prone, further driving up operating costs and hampering the customer experience.

This is why more and more insurance companies are looking towards artificial intelligence (AI) to automate claims processes and support claims decisions. Today’s advanced systems and data science techniques help insurance companies to process claims more rapidly, so that they can settle valid ones in less time and dismiss those that are invalid claims with precision.

AI enables an insurer to use massive volumes of data from multiple data points to assess claims in real-time. The system can use the data to identify risk factors and hidden customer behaviours to flag claims that should be investigated further before payment. For example, the dataset could highlight when there’s possibility that the customer is inflating their claim.

Automating more and more claims

The system could flag claims as high risk or low risk, allowing fast or even instant settlement for lower risk claims. This would give an enormous boost to customer satisfaction, while allowing claims specialists to focus their energy on the cases that need human judgement. As the system gets smarter through machine learning, a higher proportion of claims could be paid without human intervention.

AI can also help an insurance company to reduce claims wastage by identifying prospects or policyholders that are more likely to claim. This can help the insurer to price premiums more appropriately for high-risk customers. It can also enable the insurer to intervene early for customers who are more likely to claim, for example, alerting them to adjust home security or driving behaviour in response to risk.

AI can predict the claim amount, along with the causes of claim with detailed information. This helps build an appropriate strategy to reduce claim settlement time and improve precision of risk assessment upfront. Importantly, today’s data science and AI isn’t a black box—it enables insurers to explain to customers how decisions that affect their lives were made.

Accurate and prompt decision-making

AI in insurance is maturing fast, enabling insurers to take prompt and accurate decisive actions that minimise loss due to fraud and reduce costs. Today’s technology lets insurers develop and operationalise machine learning models that generate predictive insights within hours. This results in efficient claims management, reduced fraud, and a better customer experience.

*Bryan McLachlan is the Managing Director: Africa at CyborgIntell.

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